Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Canada - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Canada, seasonally-unadjusted nominal GDP was 793,974,000,000 units of local currency in 2026-Q1, compared to 836,992,000,000 in the previous quarter. This represents a reduction of 5.14 percent.
Sample. There are 261 records overall in the quarterly time series shown in the chart above. The series covers the period stretching from March 1961 to March 2026.
History. Here are a few simple statistics computed on the whole sample: GDP was equal on average to 255,674,666,667 units of local currency; it reached its highest level of 848,364,000,000 in September 2025; it hit a trough of 9,514,000,000 in March 1961.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-09-30 | 848364000000.0 |
| 2025-12-31 | 836992000000.0 |
| 2026-03-31 | 793974000000.0 |
Heads-up. To make your life easier, we organize indicators into worksheets and datasets. By scrolling down, you will discover how we arranged further information related to the statistics found here.
Not for investment purposes. Content provided on this web site is not meant for investment purposes or any other financial decision. Users should obtain expert advice and perform independent analysis before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Canada |
| Economic concept | Flow |
| Data type | Nominal aggregate |
| Seasonally adjusted | No |
| Deflation method | Current prices |
| Rescaling | None |
| Measure type | Level |
| Frequency | Quarterly |
| Unit | Units of local currency |
| Source | International Monetary Fund |
| Source type | International organization |
| Data licence | Free reuse subject to conditions |
| Other information | Not available |
| FSR temporal aggregation code | SM03 |
Series in the same data set
Discover the other time series included in this data set.